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Record W4391747924 · doi:10.54648/trad2023040

Europe’s GI Policy and New World Countries

2023· article· en· W4391747924 on OpenAlexaboutno aff
Hazel V. J. Moir

Bibliographic record

VenueJournal of World Trade · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceInternational tradeBusiness

Abstract

fetched live from OpenAlex

Trade negotiations between the European Union (EU) and Australia and New Zealand (NZ) provide the opportunity to revisit the ongoing clash between EU and New World ( United States of America (USA), Canada, Australia, NZ etc.) countries over geographical indications (GIs). Since the EU-Canada negotiations, the EU has increased its GI demands and the Australia and NZ negotiations provide the first opportunity to assess these. NZ has agreed to privileges that exceed those in the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS) and has fewer safeguards for NZ producers than were achieved in Canada. The EU’s GI demands to Australia are scrutinized in terms of competition, rule of law and consumer information criteria, providing a basis for considering how Australia should respond. A particular focus is the problematic issues raised in the demand that specific GI names be listed in the treaty without proper review and opposition procedures. Questions are also raised about the accuracy of EU GI labels and the relative merit of EU GI policy compared to certification mark GIs to promote regional development. On this basis it is suggested that Australia should reject a number of the EU’s GI demands as these lead to approving product labels which are deceptive for consumers Geographical indications, European Union, trade policy, regional development, consumer Information, food labelling, intellectual property

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0100.007
Open science0.0020.004
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0090.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.227
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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Same venueJournal of World TradeSame topicOrganic Food and AgricultureFrench-language works237,207